Mikic, N. | Search bioRxiv

bioRxiv2025

A New Method for Optimal Placement of Tumor Treating Fields Electrodes

OverviewTumor Treating Fields (TTFields) provide a non-invasive treatment option for newly diagnosed glioblastoma. While optimization of electrode placement is important to increase treatment efficacy, clinical therapy planning is done using an undisclosed and proprietary software (NovoTAL(R)), which is clinically unvalidated. This study investigates a new computational approach for optimizing TTFields electrode placement and is compared to the current clinical standard. MethodsWe developed a new computational pipeline integrating patient-specific anatomical data to optimize electrode configurations in five representative glioblastoma cases with diverse tumor locations and sizes. Two optimization strategies were employed: one maximizing electric field intensity at the tumor, and another enhancing coverage of the adjacent brain while maintaining sufficient tumor intensity. Results were compared to electrode placements generated by NovoTAL(R). Additional simulations with artificial tumors assessed the effects of tumor size and location. ResultsOptimized electrode placements improved electric field intensity in tumors by 18%-34% compared to the clinical standard. Coverage-weighted optimizations provided broader field coverage without significantly compromising tumor intensity. Smaller or surface-adjacent tumors benefited most from optimization, achieving precise targeting and enhanced coverage. Extensive randomized placement analyses highlighted the superior performance of the optimized configurations. Analysis of artificial models showed consistent improvements across varying tumor locations and sizes. ConclusionPersonalized optimization of TTFields electrode placement significantly improves electric field targeting of tumors and adjacent brain regions. This approach outperforms standardized planning software and clinical practices and supports future development of adaptive, automated strategies for individualized TTFields therapy in glioblastoma. Keypoints- Optimized TTFields array placement enhanced field intensity by 18-34% vs. clinical standard. - Optimized TTFields planning improved field coverage in tumor-adjacent regions. - Optimized TTFields planning outperformed standard methods and random placement. Importance of the studyTTFields are increasingly used as adjuvant therapy for glioblastoma. However, current individualized treatment planning relies on proprietary, undisclosed, and clinically unvalidated software, limiting transparency, optimization, and innovation in the field. This study introduces an individualized, semi-automated, and open-source method for optimal electrode placement based on standard MRI data, addressing a critical need for validated and adaptable planning tools. Our approach increased field intensity in tumors by 18-34% and achieved broader coverage compared to the standard clinical tool (NovoTAL(R)), without compromising therapeutic strength. Notably, the method also consistently outperformed extensive random electrode placements across diverse tumor types and sizes, highlighting its robustness and ability to achieve true optimal configurations. Open-source availability enhances reproducibility and clinical translation, representing a significant step toward more effective, individualized TTFields therapy. This advancement has the potential to improve outcomes for glioblastoma patients and underscores the importance of technology validation in neuro-oncology.

neuroscience↗

bioRxiv2024

Glioblastoma cells imitate neuronal excitability in humans

BackgroundGlioblastomas are renowned for their pronounced intratumoral heterogeneity, characterized by a diverse array of plastic cell types. However, the physiological and transcriptomic features of the cells residing in the invasive leading edge (LE), including both neurons and glioblastoma cells (GBCs), remain unclear, challenging our comprehension of the glioblastoma pathophysiology. MethodsTo elucidate molecular and morphophysiological features of LE cells, we established an experimental workflow enabling the investigation of GBCs and neurons within cancer-infiltrated organotypic tissue specimens from the same patients. With this approach, we characterized the electrophysiological properties of cells in the neocortical tumor LE (LE cells). We further performed single-cell Patch-seq experiments, enabling transcriptomic analysis of electrophysiologically recorded LE cells. ResultsUpon depolarization, 58% of LE cells exhibited aberrant action potentials (aAPs). Electrophysiological assessment showed that a subset of GBCs generated aAPs, with no significant differences in aAP properties compared to LE neurons. Transcriptomic analysis of 144 LE cells revealed four transcriptomic clusters, including two GBC populations and two neuronal populations. LE GBCs exhibited diverse cellular states, including mesenchymal-like, astrocyte-like, neural progenitor-like, and oligodendrocyte-precursor cell-like phenotypes. Notably, LE GBCs exhibiting aAPs displayed reduced mitotic pathway activity and developmental regulatory ion channel CaV1.2. Cell-cell interaction analysis illustrates a higher signaling interaction between aAP LE cells compared to no-aAP LE cells. ConclusionIn summary, we find comparable electrical properties between neurons and a subset of GBCs in the leading edge, suggesting an active electrophysiological role of GBCs in the tumors pathophysiology. Key PointsO_LIHuman organotypic slice cultures enable long-term functional investigation of glioblastoma cells. C_LIO_LIGBCs and neurons in the LE exhibit similar aAPs. C_LIO_LILE GBCs display heterogeneous cellular states, with reduced proliferation signaling in aAP GBCs. C_LI Importance of studyThis study sheds light on the diverse pathophysiological and molecular features of cells in the neocortical infiltration zone of glioblastoma. By utilizing in vitro organotypic human brain slice cultures, a reliable platform for longitudinal observation, we unveiled the dichotomy of the electrical properties of LE cells. More than half of LE cells display aAP, contradicting findings from cultured tumor cells and animal models. Patch-seq analysis confirmed that both GBCs and neurons in the LE generate aAPs with indistinguishable electrical properties. aAP GBCs showed higher cell-cell interactions. We find aAP GBCs to express reduced proliferation signaling compared to no-aAP GBCs, suggesting a non-dividing and potentially more plastic cell state. These findings point to the electrical-active GBCs as an important attribute of the LE, linking the electrophysiological properties with functional implications, and implicate an active role of electrophysiological changes of GBCs in tumor pathophysiology.

cancer biology↗